Education Requirements:

• Relevant bachelor's degree

• Advanced degree

Experience Requirements:

• 5+ years of professional experience

• Proficiency with C++14

• Experience with CUDA programming and parallelization of algorithms

• Experience writing TensorRT plugins

• Comfortable using collaborative development tools such as Git and Jira

Other Requirements:

• Strong written and verbal technical communication skills

• Positive, team player mindset

• Autonomy or robotics experience

• Safety critical system development

• Experience with deep learning frameworks such as PyTorch or TensorFlow

Responsibilities:

• Be a part of the team bringing L4 autonomous semi-trucks to market

• Work on the cutting edge of autonomy, optimizing deep learning models for execution on embedded NVIDIA GPUs

• Develop custom CUDA kernels and TensorRT plugins for perception and planning algorithms

• Collaborate with domain experts across the autonomy stack, influencing development, and helping deploy models to truck

• Identify and work to reduce system performance bottlenecks

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• AD+D and Life Insurance

Education Requirements:

• Bachelor’s or Master’s degree in Computer Science, Systems Engineering, Robotics, or a related technical field

Experience Requirements:

• 10+ years of engineering leadership experience

• 5+ years managing large-scale system integration or test teams in complex environments (e.g., autonomy, automotive, aerospace, or robotics)

• Strong understanding of full-stack software systems, embedded platforms, and cross-functional integration practices

• Demonstrated experience leading teams through rapid scaling, tight timelines, and evolving organizational priorities

• Excellent communication, conflict resolution, and stakeholder management skills

Other Requirements:

• A hands-on, execution-focused mindset and the ability to drive clarity and accountability across teams

• Background in autonomous systems or ADAS feature development

• Experience with system bring-up on physical test platforms or vehicles

• Familiarity with HIL systems, ROS/ROS2, safety-critical system testing, or CI/CD infrastructure

• Exposure to defect management, test automation, or metrics-driven engineering practices

Responsibilities:

• Lead a multidisciplinary team responsible for software and hardware integration across the autonomy stack and vehicle platform

• Own the bring-up process of software systems on vehicles and HIL platforms, ensuring successful deployment and operational readiness

• Partner with software, test, validation, and release teams to define integration priorities, debug system-level issues, and streamline handoffs

• Develop and scale frameworks for system testing, defect triage, release qualification, and performance tracking

• Provide visibility to program milestones, system maturity, and integration health to executive stakeholders

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• Company-wide holiday office closures

Education Requirements:

• Master's degree in computer science, data science, artificial intelligence or related field

• PhD degree

Experience Requirements:

• 6+ years of professional experience (with Master's)

• 4+ years of experience (with PhD)

• Scientific understanding of robotics learned behaviors

• Experience with learning from or validating in simulated environments

• Mastery of Python and Pytorch, with the ability to transition research level code to production and deployment ready standards

Other Requirements:

• Project Management experience in autonomous driving projects

• 2+ years of people leadership experience

• Experience with relevant NVIDIA libraries and frameworks, such as CUBLAS, CuDNN, and NPP

• Experience with Ray

Responsibilities:

• Taking the charge on the delivery of learned behavior algorithms

• Collaborates with other management and teams as needed to meet goals, monitor team performance, and achieve objectives

• Responsible for understanding the software or system technical domain of their assigned team

• Accountable and responsible for career development and coaching of the team

• Accountable and responsible for performance management of their team

Education Requirements:

• Bachelor’s or Master’s degree in Electrical Engineering, Mechatronics, or a related field

Experience Requirements:

• 3+ years of experience in electrical design for complex electromechanical systems, preferably in automotive, robotics, or aerospace

• Strong understanding of vehicle power architecture, including 12V/24V systems, DC power routing, power protection, and load management

• Familiarity with CAN/LIN bus protocols, Automotive Ethernet (100/1000BASE-T1), and coaxial transmission (e.g., for cameras or radar)

• Experience with harness design tools (Zuken preferably) and/or PCB design tools

• Proficient in debugging electrical systems using lab equipment such as oscilloscopes, logic analyzers, and power analyzers

Other Requirements:

• Experience writing, managing, and validating technical requirements in a systems engineering environment

• Comfortable working in a hands-on development and testing environment, including lab and vehicle-based work

Responsibilities:

• Design and document low- and high-voltage vehicle wiring systems, including compute and sensor harnessing

• Develop detailed schematics and/or PCB layouts for power distribution, sensor interfacing, and control modules

• Specify and integrate vehicle power distribution systems, including fusing, grounding, power converters, and relays

• Design and troubleshoot automotive communication networks, including CAN, LIN, Automotive Ethernet, and coaxial signal paths (e.g., for cameras or radar)

• Create and manage detailed harness drawings including connector selection, wire sizing, shielding, and breakout strategies

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• Company-wide holiday office closures

Education Requirements:

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field

• Master’s degree

• PhD

Experience Requirements:

• 0–4 years of experience (with Bachelor’s)

• 0–2 years (with Master’s)

• 0–2 years (with PhD)

• Strong programming skills in C++

• Familiarity with Linux development environments

Other Requirements:

• Exposure to CUDA, GPU programming concepts, or machine learning frameworks (e.g., PyTorch)

• Eagerness to learn, contribute, and grow in an applied ML engineering environment

• Internship or project experience involving distributed systems, GPU programming, or embedded software

Responsibilities:

• Develop and maintain components of the App Engine runtime and SDK supporting ML workloads on embedded GPUs

• Assist in implementing message-passing and data handling between distributed compute nodes

• Contribute to testing, debugging, and performance tuning of ML integration features

• Work closely with senior engineers to learn and apply best practices in GPU programming and embedded ML deployment

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• Company-wide holiday office closures

Education Requirements:

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field

• Master’s degree

• PhD

Experience Requirements:

• 4+ years of experience (with Bachelor’s)

• 2+ years (with Master’s)

• 1+ years (with PhD)

• Proficiency in C++ (C++14 or newer)

• Linux development

Other Requirements:

• Hands-on experience with CUDA

• Understanding of parallel programming, GPU acceleration, or real-time systems

• Strong problem-solving skills and ability to collaborate in a fast-paced environment

• Familiarity with PCIe, Ethernet-based interconnects, or embedded device programming

• Familiarity with and at least one ML framework (e.g., PyTorch)

Responsibilities:

• Implement and optimize software components supporting distributed execution of ML models on embedded GPU platforms

• Contribute to message-passing, resource management, and runtime feature development for the App Engine SDK

• Profile and optimize GPU utilization, reducing latency and maximizing throughput for ML workloads

• Collaborate with feature teams to integrate and validate App Engine functionality in vehicle and simulation environments

• Maintain clean, efficient C++ code and unit/integration tests

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• Company-wide holiday office closures

Education Requirements:

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Robotics, or a related technical field

Experience Requirements:

• 3+ years of full-cycle people management experience

• Deep technical expertise with CUDA, GPU parallel computing, and inference optimization

• Strong proficiency in C++ and Linux-based development with knowledge of real-time systems

• Experience with ML frameworks (PyTorch, TensorRT, ONNX) and model deployment pipelines

• Proven leadership managing software engineering teams in complex, cross-functional environments

Other Requirements:

• Strong understanding of system-level integration and safety-critical requirements

• Ability to thrive in a fast-paced, dynamic, and highly collaborative environment

• Hands-on leadership style — comfortable diving into technical discussions and design reviews

• Experience building or managing application/middleware frameworks for production AV or ADAS systems

• Familiarity with ISO 26262, ASPICE, or other regulated safety standards

Responsibilities:

• Lead and grow a team building the application framework that integrates deep learning models into Torc’s autonomy stack

• Drive technical execution across key focus areas: CUDA optimization, GPU resource management, model conversion pipelines (PyTorch, TensorRT, ONNX), and real-time system integration

• Ensure reliability, determinism, and scalability across multi-sensor autonomous driving workloads

• Partner with cross-functional teams (Perception, Planning, Systems, Validation, Hardware, Safety) to align technical direction and integration priorities

• Mentor, coach, and develop engineers while cultivating a collaborative, high-trust team culture

Benefits:

• A competitive compensation package that includes a bonus component and stock options

• 100% paid medical, dental, and vision premiums for full-time employees

• 401K plan with a 6% employer match

• Flexibility in schedule and generous paid vacation (available immediately after start date)

• AD+D and Life Insurance

Education Requirements:

• Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or related field

• Master’s degree preferred

Experience Requirements:

• 7+ years of relevant engineering experience in mechanical, hardware integration, or automotive systems roles

• 3+ years of experience managing or leading technical engineering teams in a hands-on environment

• Strong foundation in mechanical product development, system integration, or vehicle-level design

• Proven ability to lead hybrid teams (engineers + technicians) toward complex build and delivery goals

• Skilled in requirements management, DFMEA processes, design documentation, engineering analysis, and iterative prototyping

Other Requirements:

• Effective communicator, able to work across disciplines and manage trade-offs under tight timelines

• Experience with 3D CAD tools (e.g., CATIA, NX, SolidWorks), wiring schematics, or electrical integration

• Background in prototype or low-volume hardware integration for automotive, robotics, or aerospace applications

• Experience interfacing with contract manufacturers or build shops

• Familiarity with fast-paced environments involving rapidly changing requirements and tight turnarounds

Responsibilities:

• Lead day-to-day execution for prototype integration and low-volume builds of autonomous trucking systems and supporting infrastructure

• Oversee a blended team of engineers and technicians, ensuring seamless alignment between system requirements, DFMEA findings, and physical implementation

• Own and evolve internal engineering processes for mechanical and electrical design, requirements management, integration reviews, prototype validation, and feedback to upstream design teams

• Provide hands-on technical leadership in areas such as mechanical packaging, wire harness routing, design reviews, and vehicle bring-up

• Manage staffing, performance management, coaching, career development, and compensation planning for a ~6–8 person team